Application of temporal streamflow descriptors in hydrologic model parameter estimation

This paper presents a parameter estimation approach based on hydrograph descriptors that capture dominant streamflow characteristics at three timescales (monthly, yearly, and record extent). The scheme, entitled hydrograph descriptors multitemporal sensitivity analyses (HYDMUS), yields an ensemble of model simulations generated from a reduced parameter space, based on a set of streamflow descriptors that emphasize the timescale dynamics of streamflow record. In this procedure the posterior distributions of model parameters derived at coarser timescales are used to sample model parameters for the next finer timescale. The procedure was used to estimate the parameters of the Sacramento soil moisture accounting model (SAC-SMA) for the Leaf River, Mississippi. The results indicated that in addition to a significant reduction in the range of parameter uncertainty, HYDMUS improved parameter identifiability for all 13 of the model parameters. The performance of the procedure was compared to four previous calibration studies on the same watershed. Although our application of HYDMUS did not explicitly consider the error at each simulation time step during the calibration process, the model performance was, in some important respects, found to be better than in previous deterministic studies. Copyright 2005 by the American Geophysical Union

Bayesian Analysis of the Impact of Rainfall Data Product on Simulated Slope Failure for North Carolina Locations

In the past decades, many different approaches have been developed in the literature to quantify the load-carrying capacity and geotechnical stability (or the factor of safety, Fs) of variably saturated hillslopes. Much of this work has focused on a deterministic characterization of hillslope stability. Yet, simulated Fs values are subject to considerable uncertainty due to our inability to characterize accurately the soil mantles properties (hydraulic, geotechnical, and geomorphologic) and spatiotemporal variability of the moisture content of the hillslope interior. This is particularly true at larger spatial scales. Thus, uncertainty-incorporating analyses of physically based models of rain-induced landslides are rare in the literature. Such landslide modeling is typically conducted at the hillslope scale using gauge-based rainfall forcing data with rather poor spatiotemporal coverage. For regional landslide modeling, the specific advantages and/or disadvantages of gauge-only, radar-merged and satellite-based rainfall products are not clearly established. Here, we compare and evaluate the performance of the Transient Rainfall Infiltration and Grid-based Regional Slope-stability analysis (TRIGRS) model for three different rainfall products using 112 observed landslides in the period between 2004 and 2011 from the North Carolina Geological Survey database. Our study includes the Tropical Rainfall Measuring Mission (TRMM) Multi-satellite Precipitation Analysis Version 7 (TMPA V7), the North American Land Data Assimilation System Phase 2 (NLDAS-2) analysis, and the reference truth Stage IV precipitation. TRIGRS model performance was rather inferior with the use of literature values of the geotechnical parameters and soil hydraulic properties from ROSETTA using soil textural and bulk density data from SSURGO (Soil Survey Geographic database). The performance of TRIGRS improved considerably after Bayesian estimation of the parameters with the DiffeRential Evolution Adaptive Metropolis (DREAM) algorithm using Stage IV precipitation data. Hereto, we use a likelihood function that combines binary slope failure information from landslide event and null periods using multivariate frequency distribution-based metrics such as the false discovery and false omission rates. Our results demonstrate that the Stage IV-inferred TRIGRS parameter distributions generalize well to TMPA and NLDAS-2 precipitation data, particularly at sites with considerably larger TMPA and NLDAS-2 rainfall amounts during landslide events than null periods. TRIGRS model performance is then rather similar for all three rainfall products. At higher elevations, however, the TMPA and NLDAS-2 precipitation volumes are insufficient and their performance with the Stage IV-derived parameter distributions indicates their inability to accurately characterize hillslope stability

Simulation of the spatio-temporal extent of groundwater flooding using statistical methods of hydrograph classification and lumped parameter models

This article presents the development of a relatively low cost and rapidly applicable methodology to simulate the spatio-temporal occurrence of groundwater flooding in chalk catchments. In winter 2000/2001 extreme rainfall resulted in anomalously high groundwater levels and groundwater flooding in many chalk catchments of northern Europe and the southern United Kingdom. Groundwater flooding was extensive and prolonged, occurring in areas where it had not been recently observed and, in places, lasting for 6 months. In many of these catchments, the prediction of groundwater flooding is hindered by the lack of an appropriate tool, such as a distributed groundwater model, or the inability of models to simulate extremes adequately. A set of groundwater hydrographs is simulated using a simple lumped parameter groundwater model. The number of models required is minimized through the classification and grouping of groundwater level time-series using principal component analysis and cluster analysis. One representative hydrograph is modelled then transposed to other observed hydrographs in the same group by the process of quantile mapping. Time-variant groundwater level surfaces, generated using the discrete set of modelled hydrographs and river elevation data, are overlain on a digital terrain model to predict the spatial extent of groundwater flooding. The methodology is applied to the Pang and Lambourn catchments in southern England for which monthly groundwater level time-series exist for 52 observation boreholes covering the period 1975–2004. The results are validated against observed groundwater flood extent data obtained from aerial surveys and field mapping. The method is shown to simulate the spatial and temporal occurrence of flooding during the 2000/2001 flood event accurately

Stochastic inverse modeling of transient laboratory-scale three-dimensional two-phase core flooding scenarios

We develop a comprehensive and efficient workflow for a stochastic assessment of key parameters governing two-phase flow conditions associated with core-scale experiments. We rely on original and detailed datasets collected on a Berea sandstone sample. These capture the temporal evolution of pressure drop across the core and three-dimensional maps of phase saturations (determined via X-ray CT) in oil- and brine-displacement flooding scenarios characterized by diverse brine/oil viscosity contrasts. Such experiments are used as a test-bed for the proposed stochastic model calibration strategy. The latter is structured across three main steps: (i) a preliminary calibration, aimed at identifying a behavioral region of the model parameter space; (ii) a Global Sensitivity Analysis (GSA), geared towards identification of the relative importance of model parameters on observed model outputs and assessment of non-influential parameters to reduce dimensionality of the parameter space; and (iii) a stochastic inverse modeling procedure. The latter is based on a differential-evolution genetic algorithm to efficiently explore the reduced parameter space stemming from the GSA. It enables one to obtain a probabilistic description of the relevant model parameters through their frequency distributions conditional on the detailed type of information collected. Coupling GSA with a stochastic parameter estimation approach based on a genetic algorithm of the type we consider enables streamlining the procedure and effectively cope with the considerable computational efforts linked to the two-phase scenario considered. Results show a remarkable agreement with experimental data and imbue us with confidence on the potential of the approach to embed the type of rich datasets considered towards model parameter estimation fully including uncertainty

Calibration of a conceptual rainfall-runoff model for flood frequency estimation by continuous simulation

An approach is described to the calibration of a conceptual rainfall-runoff model, the Probability Distributed Model (PDM), for estimating flood frequencies at gauged sites by continuous flow simulation. A first step was the estimation of routing store parameters by recession curve analysis. Uniform random sampling was then used to search for parameter sets that produced simulations achieving the best fit to observed, hourly flow data over a 2-year period. Goodness of fit was expressed in terms of four objective functions designed to give different degrees of weight to peaks in flow. Flood frequency results were improved, if necessary, by manual adjustment of parameters, with reference to peaks extracted from the entire hourly flow record. Although the primary aim was to reproduce observed peaks, consideration was also given to finding parameter sets capable of generating a realistic overall characterization of the flow regime. Examples are shown where the calibrated model generated simulations that reproduced well the magnitude and frequency distribution of peak flows. Factors affecting the acceptability of these simulations are discussed. For an example catchment, a sensitivity analysis shows that there may be more than one set of parameter values well suited to the simulation of peak flows

Impacts of upland open drains upon runoff generation: a numerical assessment of catchment-scale impacts

Shallow upland drains, grips, have been hypothesized as responsible for increased downstream flow magnitudes. Observations provide counterfactual evidence, often relating to the difficulty of inferring conclusions from statistical correlation and paired catchment comparisons, and the complexity of designing field experiments to test grip impacts at the catchment scale. Drainage should provide drier antecedent moisture conditions, providing more storage at the start of an event; however, grips have higher flow velocities than overland flow, thus potentially delivering flow more rapidly to the drainage network. We develop and apply a model for assessing the impacts of grips on flow hydrographs. The model was calibrated on the gripped case, and then the gripped case was compared with the intact case by removing all grips. This comparison showed that even given parameter uncertainty, the intact case had significantly higher flood peaks and lower baseflows, mirroring field observations of the hydrological response of intact peat. The simulations suggest that this is because delivery effects may not translate into catchment-scale impacts for three reasons. First, in our case, the proportions of flow path lengths that were hillslope were not changed significantly by gripping. Second, the structure of the grip network as compared with the structure of the drainage basin mitigated against grip-related increases in the concentration of runoff in the drainage network, although it did marginally reduce the mean timing of that concentration at the catchment outlet. Third, the effect of the latter upon downstream flow magnitudes can only be assessed by reference to the peak timing of other tributary basins, emphasizing that drain effects are both relative and scale dependent. However, given the importance of hillslope flow paths, we show that if upland drainage causes significant changes in surface roughness on hillslopes, then critical and important feedbacks may impact upon the speed of hydrological response

New Measurements of Fine-Scale CMB Polarization Power Spectra from CAPMAP at Both 40 and 90 GHz

We present new measurements of the cosmic microwave background (CMB) polarization from the final season of the Cosmic Anisotropy Polarization MAPper (CAPMAP). The data set was obtained in winter 2004-2005 with the 7 m antenna in Crawford Hill, New Jersey, from 12 W-band (84-100 GHz) and 4 Q-band (36-45 GHz) correlation polarimeters with 3.3' and 6.5' beamsizes, respectively. After selection criteria were applied, 956 (939) hours of data survived for analysis of W-band (Q-band) data. Two independent and complementary pipelines produced results in excellent agreement with each other. A broad suite of null tests as well as extensive simulations showed that systematic errors were minimal, and a comparison of the W-band and Q-band sky maps revealed no contamination from galactic foregrounds. We report the E-mode and B-mode power spectra in 7 bands in the range 200 < l < 3000, extending the range of previous measurements to higher l. The E-mode spectrum, which is detected at 11 sigma significance, is in agreement with cosmological predictions and with previous work at other frequencies and angular resolutions. The BB power spectrum provides one of the best limits to date on B-mode power at 4.8 uK^2 (95% confidence).Comment: 19 pages, 17 figures, 2 tables, submitted to Ap

IMPACTS OF CLIMATE AND REGULATION ON ICE-JAM FLOODING OF NORTHERN RIVERS AND THEIR INLAND DELTAS

In cold region environments, ice-jam floods (IJFs) are important hydrological and hydraulic events that play an important role in floodplain ecology but also pose a major concern for citizens, authorities, insurance companies and government agencies, primarily because they can result in high water depths in rivers that can exceed levees leading to devastating floods. In the past 35 years, there have been significant advances in river ice hydrology. However, understanding on several aspects of IJFs still remains limited. Little work has been carried out on investigating how the frequency and severity of IJFs have been changing or might change in the future. Similarly, IJF delineation remains a significant challenge even for streams and small rivers. There is also still substantial progress to be made in quantifying the effects of climate variability and regulation on IJFs. This dissertation addresses some of these existing knowledge gaps. First, it reviews the recent advances in IJF research and identifies existing gaps, challenges and opportunities. With a changing environment, there are implications for river ice processes and this dissertation work investigates some of the potential implications particularly how the timing and magnitude of breakup flows that lead to IJFs are changing at local and regional levels. Literature review shows IJF research has been highly site specific but this dissertation also offers regional and global perspectives. Climate and anthropogenic factors are likely to have unequal localized effects. Some regions might be more resilient and others, such as high latitude northern regions, might be more vulnerable. Thus, local implications for river ice processes and current and future probabilities of IJFs are assessed for two river basins in western Canada. The findings from the Athabasca River at the town of Fort McMurray show that the probability of ice-jam flooding in the future will be lower but extreme IJF events are still probable. The results from the town of the Peace River in western Canada suggest that regulation can have larger role in increasing IJF risks as water levels during ice-jam staging at the town were found to be higher due to regulation compared to naturalized conditions. However, regulation also offers a possibility of reducing IJF risks and promoting sustainability in regulated rivers. It is demonstrated that with appropriate reservoir operation scheme, it is feasible to minimize flood risk at upstream communities and maximize flood potential at downstream deltaic ecosystem, where it is essential. As ice-jam flooding, both at present and in the future, remains a major concern in northern IJF prone communities, a probability curve of overbank flow based on breakup discharge is presented. Using a stochastic approach to evaluate the impacts of different magnitudes of discharge on IJF is a novel approach, and serves as an important benchmark for future IJF studies, especially for estimating future IJF probabilities. One other important methodological contribution is the introduction of a probability-based extension of the hydro-technical modelling approach that couples physically-based hydrologic and hydraulic models to assess the relative impacts of climate and regulation within a stochastic framework. Thus, the findings of this work have advanced our understanding of impacts of climate and regulation on ice-jam flooding of northern rivers and their inland deltas. As the first step in reducing flood risks, identifying, understanding and quantifying flood hazard will improve our ability to reduce risks and increase resiliency